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Biomedical Informatics Insights

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Rule-based and Lightly Supervised Methods to Predict Emotions in Suicide Notes

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Publication Date: 30 Jan 2012

Type: Original Research

Journal: Biomedical Informatics Insights

Citation: Biomedical Informatics Insights 2012:5 (Suppl. 1) 185-193

doi: 10.4137/BII.S8953

Abstract

This paper describes the Duluth systems that participated in the Sentiment Analysis track of the i2b2/VA/Cincinnati Children’s 2011 Challenge. The top Duluth system was a rule-based approach derived through manual corpus analysis and the use of measures of association to identify significant ngrams. This performed in the median range of systems, attaining an F-measure of 0.45. The second system was automatically derived from the most frequent bigrams unique to one or two emotions. It achieved an F-measure of 0.36. The third system was the union of the first two, and reached an F-measure of 0.44.


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